DeepEP

Headlines · 2

1. 3d
   Moore Threads Open-Sources Megatron-MUSA-Titan for Large-Scale MoE Training

   Moore Threads announced the open-sourcing of Megatron-MUSA-Titan, a large-model training infrastructure project adapted for the company’s MUSA platform and full-function GPUs. IT之家 reported that it targets trillion-parameter MoE pretraining and reinforcement learning on clusters with 10,000 GPUs. The project supports blockwise FP8 training and can work with the DeepEP and ACE asynchronous communication engines to overlap expert parallelism and computation. Moore Threads said the project had been used in continued trillion-parameter MoE pretraining on its 10,000-GPU-scale cluster and supports coordination with slime and miles, Megatron training, and SGLang sample generation. Its reported model FLOPS utilization and long-running stability were not independently verified in the supplied reports.

   IT之家 AI · 🔥 0
2. 7d
   SGLang Reports Matching or Beating DeepInfer

   DeepSeek open-sourced DeepInfer, the inference engine behind its own service, along with related kernels. In project-run tests using DeepInfer’s benchmarks and the same hardware, SGLang reached up to 1.04x prefill throughput on four GB300 or four B300 GPUs and cut decode step time by as much as 7.4% on 64 GB300 GPUs, according to the SGLang report. A 36氪 report said vLLM also approached or partly exceeded DeepInfer under its disclosed configurations. The comparisons used project-reported results and differing workloads and measurement methods.

   LMSYS Blog · 🔥 0

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